It is also possible to encourage models to learn fair representations by only using the data. Among the simplest methods, a reweighting factor can be added to the loss so as to emphasize the discriminated samples [1]}. An alternative is to resample the training dataset in different manners: by undersampling the dominant groups to encourage the model to learn more general rules [2]}, by oversampling the discriminated groups [3]}, by using a technique similar to MixUp [4]} to interpolate between dominant and minority groups [5]}, or by generating more samples of the discriminated groups through generative models [6]}, [7]}, [8]}.
